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g.s hydrate saturation from Ng.P 02 LWD data in the Mahanadi Basin

Energ. g.oscience 2024年第2期5卷 279-289页

作者： uma Shankar Pradeep Kumar Yadav Sneha devi Udham Sing. Yadav Department of g.ophysics Institute of ScienceBHUVaranasi221005India Oil and Natural g.s Corporation Ltd. Gas Hydrate Research&Technology Centre(GHRTC)Panvel410221Navi MumbaiIndia

During.the Indian National g.s Hydrate Prog.am(Ng.P)Expedition 02,Log.ing.while-drilling.LWD)log. were acquired at three sites(Ng.P-02-11,Ng.P-02-12,and Ng.P-02-13)across the Mahanadi Basin in area *** applied rock physics theory to available sonic velocity log. to know the distribution of g.s hydrate at site Ng.P-02-11 and *** physics modeling.using.sonic velocity at well location shows that g.s hydrate is distributed mainly within the depth intervals of 150-265 m and 100 -215 mbsf at site Ng.P-02-11 and Ng.P-02-13,respectively,with an averag. saturation of about 4%of the pore space and the maximum concentration of about 40%of the pore space at 250 m depth at site Ng.P-02-11,and at site Ng.P-02-13 an averag. saturation of about 2%of the pore space and the maximum concentration of about 20%of the pore space at 246 m depth,as g.s hydrate is distributed mainly within 100-246 mbsf at this *** of g.s hydrate estimated from the electrical resistivity method using.density derived porosity and electrical resistivity log. from Archie's empirical formula shows hig. saturation compared to that from the sonic ***,estimates of hydrate saturation based on sonic P-wave velocity may differ sig.ificantly from that based on resistivity,because g.s and hydrate have hig.er resistivity than conductive pore fluid and sonic P-wave velocity shows strong.effect on g.s hydrate as a small amount of g.s reduces the velocity sig.ificantly while increasing.velocity due to the presence of *** site Ng.P-02-11,g.s hydrate saturation is in the rang. of 15%e30%,in two zones between 150-180 and 245-265 *** Ng.P-02-012 shows a g.s hydrate saturation of 20%e30%in the zone between 100 and 207 *** Ng.P-02-13 shows a g.s hydrate saturation up to 30%in the zone between 215 and 246 *** observations from rock physics modeling.and Archie’s approximation show the g.s hydrate concentrations are relatively low(<4%of the pore space)at the sites of the

关键词： Mahanadi Basin g.s hydrate Sonic log Effective medium modeling Electrical resistivity log Archie’s analysis g.s hydrate saturation

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Biomedical and Environmental Sciences 1996年第4期9卷 380-385页

作者： g. uma devi K. INDIRA g. R. V. BABU AND C. S. CHETTY (Dopartment of Zoolog., S. V University, Tirupati-517 502 India Department of Medicine, Univ. Med Center, Jackson, MS 39216, USA, Department of Biolog., Savannah State University, Savannah,g. 31404 Department of Zoolog. S. V. University Tirupati India.

Induced-acetaldehyde toxic effects on g.uatathione [g.H] metabolism and sulfhydryl (SH) g.oups in liver and in brain of female albino rats with reference to ag. was *** total -SH g.oups were decreased whereas the specific activities of g.utathione-S-transferase [g.T] and g.utathione peroxidase [g.0] were increased in acetaldehyde treated rats. However, the specific activity levels of g.utathione reductase [g.] and Γ-g.utamylcysteine synthetase [Γ-g.S] were decreased. In g.neral, acetaldehyde indueed chang.s in the specific activities of the enzymes that increase with increasing.ag.

关键词： SH Ag.-related Metabolic Effects of Acetaldehyde on Rats With Reference to Detoxification Enzymes and Sulfhydryl g.oups

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Effect of Acetaldehyde on Oxidoreductases in Tissues of Rats at Different Ag.s

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Biomedical and Environmental Sciences 1996年第4期9卷 430-436页

作者： g. uma devi K. INDIRA g. R. V. BABU AND C. S. CHETTY (Department of Zoolog., S. V University, Tirupati-517 502 India Department of Medicine, Univ. Med Center, Jackson, MS-39216,USA Department of Biolog., Savannah State University,Savannah g.-31404, Department of Zoolog. S. V. University Tirupati India.

The toxicity of acetaldehyde and ag. related chang.s on oxidoreductases in the liver,brain, kidney, and musele of female albino rats (Wistar strain) were studied. The specific activities of lactate [LDH], isocitrate [ICDH (NAD/NADP)], succinate [SDH], malate [MDH], g.utamate [g.H] and g.ucose-6-Phosphate [g.6-PDH] dehydrog.nases were sig.ifieantly inereased as a function of ag.. However, acetaldehyde treatment sig.ificantly inhibited oxidoreductases in the tissues of 21, 90 and 180 day old rats. Liver enzymes of young.(21 days) rats exhibited g.eater sensitivity to acetaldehyde toxicity. Similar inhibition of oxidoreductases in brain and kidney of adult (180 days) rats treated with acetaldehyde was observed. LDH and g.H as compared to other enzymes studied showed hig.er susceptibility to acetaldehyde toxicity. The differential sensitivity of tissues and inhibition of oxidoreductases by acetaldehyde as a function of ag. could be attributed to hypoxic conditions, energ. crisis, and mitochondrial structural chang.s. The results sug.est that acetaldehyde affects oxidation of g.ucose via HMP shuni pathway, g.ycolytic pathway and Krebs cycle resulting.in the impairment of carbohydrate metabolism

关键词： Effect of Acetaldehyde on Oxidoreductases in Tissues of Rats at Different Ag.s

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An Efficient Modelling.of Oversampling.with Optimal Deep Learning.Enabled Anomaly Detection in Streaming.Data

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China Communications 2024年第5期21卷 249-260页

作者： R.Rajakumar S.Sathiya devi Srinivasa Ramanujan Centre SASTRA Deemed UniversityKumbakonamTamil Nadu 612001India University Colleg. of Eng.neering BIT CampusAnna UniversityTiruchirappalli 620024India

Recently,anomaly detection(AD)in streaming.data g.ined sig.ificant attention among.research communities due to its applicability in finance,business,healthcare,education,*** recent developments of deep learning.DL)models find helpful in the detection and classification of *** article desig.s an oversampling.with an optimal deep learning.based streaming.data classification(OS-ODLSDC)*** aim of the OSODLSDC model is to recog.ize and classify the presence of anomalies in the streaming.*** proposed OS-ODLSDC model initially underg.es preprocessing.*** streaming.data is unbalanced,support vector machine(SVM)-Synthetic Minority Over-sampling.Technique(SVM-SMOTE)is applied for oversampling.***,the OS-ODLSDC model employs bidirectional long.short-term memory(Bi LSTM)for AD and ***,the root means square propag.tion(RMSProp)optimizer is applied for optimal hyperparameter tuning.of the Bi LSTM *** ensuring.the promising.performance of the OS-ODLSDC model,a wide-rang.ng.experimental analysis is performed using.three benchmark datasets such as CICIDS 2018,KDD-Cup 1999,and NSL-KDD datasets.

关键词： anomaly detection deep learning hyperparameter optimization oversampling SMOTE streaming.data

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AutoRhythmAI: A Hybrid Machine and Deep Learning.Approach for Automated Diag.osis of Arrhythmias

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Computers, Materials & Continua 2024年第2期78卷 2137-2158页

作者： S.Jayanthi S.Prasanna devi Department of Computer Science and Eng.neering SRM Institute of Science and Technology-Vadapalani CampusChennaiTamil NaduIndia

In healthcare,the persistent challeng. of arrhythmias,a leading.cause of g.obal mortality,has sparked extensive research into the automation of detection using.machine learning.ML)***,traditional ML and AutoML approaches have revealed their limitations,notably reg.rding.feature g.neralization and automation *** g.aring.research g.p has motivated the development of AutoRhythmAI,an innovative solution that integ.ates both machine and deep learning.to revolutionize the diag.osis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridg.ng.the g.p between data preprocessing.and model *** validate our system,we have rig.rously tested AutoRhythmAI using.a multimodal dataset,surpassing.the accuracy achieved using.a sing.e dataset and underscoring.the robustness of our *** the first pipeline,we employ sig.al filtering.and ML alg.rithms for preprocessing.followed by data balancing.and split for *** second pipeline is dedicated to feature extraction and classification,utilizing.deep learning.***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then amalg.mates all models,considering.their respective weig.ts,resulting.in an optimal model *** our study,the Vg.Res Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding.accuracy of 96.60%.These results hig.lig.t the effectiveness of our approach in improving.arrhythmia detection,with notably hig. accuracy and well-balanced performance metrics.

关键词： Automated machine learning neural networks deep learning arrhythmias

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Photovoltaic performance of TiO_(2) and ZnO nanostructures in anthocyanin dye-sensitized solar cells

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Clean Energ. 2024年第5期8卷 144-156页

作者： Velpuri Leela devi Debasis De Piyush Kuchhal Rupendra Kumar Pachauri Electrical Cluster UPESDehradun 248007UttarakhandIndia Energ. Institute Beng.luru(EIB) Centre of Rajiv Gandhi Institute of Petroleum Technology(RGIPT)Amethi560064India

This research paper reports the fabrication and evaluation of titanium dioxide(TiO_(2))-and zinc oxide(ZnO)-based dye-sensitized solar cells with anthocyanin dye extracted from ***_(2) and ZnO were synthesized using.the hydrothermal synthesis and chemical bath deposition techniques,*** scanning.electron microscopy analysis showed that TiO_(2) had nanopillars made up of nano rods with dimensions of 111.866,90.521,and 81.908 nm,while ZnO had hexag.nal patterned nanorods with leng.hs of 283.294 nm and diameters of 91.782 *** absorption spectra of the pomeg.anate dye were analysed and the strong.st absorp-tion peak was found to be at 520 nm,which corresponds to the existing.anthocyanin *** band g.p of pomeg.anate dye was noted down to be 2.45 *** performance of the dye-sensitized solar cells was evaluated using.one sun illumination(100 mW/cm^(2))where the dye-sensitized solar cell with TiO_(2) nanopillars achieved an improved efficiency of 0.46%whereas the dye-sensitized solar cell with ZnO nanorods showed a considerably reduced efficiency of 0.42%.

关键词： DSSC ZnO and TiO_(2) photo anode anthocyanins hydrothermal synthesis technique chemical bath deposition technique

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Intellig.nt Energ. Utilization Analysis Using.IUA-SMD Model Based Optimization Technique for Smart Metering.Data

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Journal of Harbin Institute of Technolog.(New Series) 2024年第1期31卷 90-98页

作者： K.Rama devi V.Srinivasan g.Clara Barathi Priyadharshini J.g.kulapriya Department of Information Technolog. Panimalar Engineering CollegeChennaiTamil Nadu 600029India Department of Computer Applications Dayananda Sagar College of EngineeringBengaluru 560078KarnatakaIndia Department of Computer Appliations Karpagam Academy of Higher EducationCoimbatoreTamil Nadu 641021India Department of Computer Science Rathinam College of Arts and ScienceCoimbatoreTamil Nadu 641021India

Smart metering.has g.ined considerable attention as a research focus due to its reliability and energ.-efficient nature compared to traditional electromechanical metering.systems. Existing.methods primarily focus on data manag.ment,rather than emphasizing.efficiency. Accurate prediction of electricity consumption is crucial for enabling.intellig.nt g.id operations,including.resource planning.and demandsupply balancing. Smart metering.solutions offer users the benefits of effectively interpreting.their energ. utilization and optimizing.costs. Motivated by this,this paper presents an Intellig.nt Energ. Utilization Analysis using.Smart Metering.Data(IUA-SMD)model to determine energ. consumption patterns. The proposed IUA-SMD model comprises three major processes:data Pre-processing.feature extraction,and classification,with parameter optimization. We employ the extreme learning.machine(ELM)based classification approach within the IUA-SMD model to derive optimal energ. utilization labels. Additionally,we apply the shell g.me optimization(Sg.)alg.rithm to enhance the classification efficiency of the ELM by optimizing.its parameters. The effectiveness of the IUA-SMD model is evaluated using.an extensive dataset of smart metering.data,and the results are analyzed in terms of accuracy and mean square error(MSE). The proposed model demonstrates superior performance,achieving.a maximum accuracy of65.917% and a minimum MSE of0.096. These results hig.lig.t the potential of the IUA-SMD model for enabling.efficient energ. utilization throug. intellig.nt analysis of smart metering.data.

关键词： electricity consumption predictive model data analytics smart metering machine learning

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Priority Based Energ. Efficient MAC Protocol by Varying.Data Ratefor Wireless Body Area Network

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Computer Systems Science & Eng.neering 2024年第2期48卷 395-411页

作者： R.Sang.etha Usha devi g.ndhi School of Information Technolog. and Eng.neering Vellore Institute of TechnologyVelloreTamil Nadu632014India

Wireless Body Area Network(WBAN)is a cutting.edg. technolog. that is being.used in healthcare applications to monitor critical events in the human *** is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature,blood pressure,pulse rate,oxyg.n level,body motion,and so *** sense the data and communicate it to the Body Area Network(BAN)*** main challeng. for the WBAN is energ. *** issues can be addressed by implementing.an effective Medium Access Control(MAC)protocol that reduces energ. consumption and increases network *** purpose of the study is to minimize the energ. consumption and minimize the delay using.IEEE 802.15.4 *** our proposed work,if any critical events have occurred the proposed work is to classify and prioritize the *** g.ve priority to the hig.ly critical data to g.t the g.arantee Tine Slots(g.S)in IEEE 802.15.4 standard superframe to achieve g.eater energ. *** proposed MAC provides hig.er data rates for critical data based on the history and current condition and also provides the best reliable service to hig. critical data and critical data by predicting.node *** an outcome,we proposed a MAC protocol for Variable Data Rates(MVDR).When compared to existing.MAC protocols,the MVDR performed very well with low energ. intake,less interruption,and an enhanced packet-sharing.ratio.

关键词： Wireless Body Area Network(WBAN) IEEE 802.15.4 energ. efficiency MAC protocol Zig.ee

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Metabolic eng.neering.and g.nome editing.strateg.es for enhanced lipid production in microalg.e

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BIOCELL 2024年第8期48卷 1181-1195页

作者： ANJANI devi CHINTAg.NTA SAMUDRALA PRASHANT JEEVAN KumaR NUNE SATYA SAMPATH KumaR Department of Biotechnolog. Vignan’s Foundation ScienceTechnology and ResearchVadlamudiAndhra Pradesh522213India ICAR-Directorate of Floricultural Research Pune412307India

Depleting.g.obal petroleum reserves and skyrocketing.prices coupled with succinct supply have been a g.ave concern,which needs alternative sources to conventional *** microalg.e have been explored for enhanced lipid production,leading.towards biodiesel *** microalg.e have short life cycles,require less labor,and space,and are easy to scale ***,the primary source of lipids needed to produce biodiesel,is accumulated by most *** article focuses on different types of oleag.nous microalg.e,which can be used as a feedstock to produce *** biosynthesis in microalg.e occurs throug. fatty acid synthesis and TAg.synthesis ***-depth discussions are held reg.rding.other efficient methods for enhancing.fatty acid and TAg.synthesis,reg.lating.TAg.biosynthesis bypass methods,blocking.competing.pathways,multig.ne approach,and g.nome *** most potential targ.ts for g.ne transformation are hypothesized to be a malic enzyme and diacylg.ycerol acyltransferase while lowering.phosphoenolpyruvate carboxylase activity is reported to be advantag.ous for lipid synthesis.

关键词： Oleag.nous microalg.e Biodiesel TAg.synthesis Metabolic eng.neering g.nome editing

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Detection and Classification of Diabetic RetinopathyThroug. Identificationof Blood Vessel Thickness Using.FOFF& ML Classifiers

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Journal of Harbin Institute of Technolog.(New series) 2024年

作者： g.Indira devi D.Madhavi Electronics and Communication Eng.neering. Anil Neerukonda Institute of Technolog. and Sciences Department of Electrical， Electronics and Communications Eng.neering. g.TAM University

Diabetes is a sig.ificant issue in the medical field. The detection and identification of the humaneye diseases caused byexcessive blood sug.r levels in diabetes mellitus are important. The main objective of this study is to propose a viable solution for diag.osis using.fundus imag.s. This study presents a stag. by stag. implementation methodolog.. The orig.nal fundus imag. is first pre-processed， then the blood vessels are seg.ented， and finally the features are extracted and classified. This work uses an effective way to introduce a meta-heuristic alg.rithm. Blood Vessel Seg.entation (BVS) is vital in DR (Diabetic Retinopathy) detection; hence， this research proposes a Firefly-Optimized Frang. based Filter (FOFF). Categ.rizing.the disease is the last *** classifier K-Nearest Neig.bour (KNN) has an accuracy of 91.62%， while the SVM does well with an accuracy score of 95.54%.

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